This invention relates to methods and apparatus for measuring the temperature of an object, in particular a sheet material, by detecting radiation emitted by the object.
Thermal imagers provide two dimensional temperature images of a scene. Typically, such devices observe and measure infrared emission from the scene, thus providing a measure of temperature without being in contact with the source. Infrared energy is emitted by all materials at temperatures above absolute zero. This energy travels in the form of electromagnetic waves with wavelengths typically in the range 0.7 microns to 20 microns. When an infrared ray is intercepted by a body which is not transparent to the infrared spectrum, it induces electronic transitions or its energy is converted into heat and the infrared rays may be observed. Infrared imaging systems convert the energy transmitted in the infrared spectrum into a visible light image.
On striking a material surface, part of the infrared energy will be absorbed, some will be reflected and the remainder transmitted through the object. Of the energy absorbed by the material, a proportion may be re-emitted. Together, these phenomena determine the “emissivity” of the material, which is defined as the ratio of energy radiated by the material to energy radiated by a black body at the same temperature. A “black body” is a hypothetical object or system which does not reflect or transmit any infrared energy incident upon it. All such radiation is absorbed and the black body re-radiates energy characteristic of its temperature only. A true black body has an emissivity of 1 but the nearest that can be achieved in practice is about 0.998, using an infrared opaque cavity with a small aperture.
Infrared temperature measurements often have to be made on targets with low or variable emissivity. This can lead to substantial errors.
One way to alleviate such errors is to aim the infra-red thermometer into a ‘cavity’ in the target. This cavity acts to a greater or lesser degree as a ‘black-body’ cavity. The effective value of the emissivity is raised and stabilised by reflections within the cavity. Measurement errors are thus reduced.
An important implementation of this idea is where a strip product is either passed over a roller or is coiled around a roller (which may be in the form of a mandrel). The cavity takes the form of a ‘wedge’ defined between the strip and the roller (or coil) and can act as a very effective black-body cavity. FIG. 1 schematically depicts two examples and indicates the location of the cavity in each case: FIG. 1a shows steel strip in a continuous annealing line and FIG. 1b shows coiling of aluminium strip in a strip mill.
Installations of this type have been made for some years using single spot infra-red thermometers.
A single-spot thermometer has the limitation that only a single ‘track’ on the strip (eg the centre-line) is monitored. It is also quite difficult to aim the instrument correctly (so as to obtain maximum emissivity enhancement) and to maintain that aim (so as to maintain a stable emissivity enhancement).
An infra-red linescanner can alternatively be used. This allows a temperature profile across the strip to be monitored. However alignment is even more difficult than for a single-spot thermometer.
A newer approach is to aim a thermal imager at the wedge. As described above, a thermal imaging device produces a two dimensional image of a scene and so this allows a temperature image of the cavity to be displayed without precise alignment of the instrument.
The region of optimally-enhanced-emissivity in the cavity can be identified by eye from the thermal image. For instance, FIG. 2 shows an example of a thermal image of a ‘wedge’ cavity formed by an aluminium strip being coiled onto a mandrel, and the region of interest is that comprising the brightest pixels (in reality they may be rendered as red, for example). However extracting temperatures from this region in real time is not easy for several reasons:
The imager is usually mounted off the side of the production line—so the wedge is not ‘square’ to the field of the imager. It is generally difficult or impossible to align the thermal imaging device ‘square’ to the cavity since it would obstruct the process line.
The location of the cavity within the image is not known a priori. Instead it depends on the precise alignment of the cavity and that of the imager.
Small changes in imager alignment cause the cavity to ‘wander’ within the image.
In some situations the cavity is not even approximately fixed in space relative to the imager. An example is the aluminium coiling situation shown in FIGS. 1b and 2 above. Here the coil ‘grows’ as strip spools on to the mandrel, and the ‘wedge’ cavity moves in space while the imager remains fixed. The wedge therefore moves appreciably within the image.
In accordance with the present invention, a method of measuring the temperature of a sheet material arranged such that the sheet material forms at least one side of a cavity so as to enhance the effective emissivity of the sheet material in the vicinity of the cavity, comprises:
a) generating a thermal image of at least part of the inside of the cavity using a thermal imaging device to detect radiation emitted by the cavity, the thermal image comprising a plurality of pixels each having a pixel value representative of radiation emitted by a respective region of the cavity;
b) identifying a first subset of the plurality of pixels whose pixel values meet predetermined criteria;
c) using the identified first subset of pixels to determine a line on the thermal image representative of optimal emissivity enhancement in the cavity; and
d) selecting a second subset of the plurality of pixels based on the determined line and generating a temperature profile along the determined line derived from the pixel values associated with each of the second subset of pixels.
By determining the line of optimal emissivity enhancement in this way and using it to generate a temperature profile, the invention greatly increases the accuracy with which the temperature of the sheet material can be monitored. The technique accurately ‘finds’ and ‘tracks’ the line of optimally-enhanced emissivity in the image and so overcomes the problems of ‘wander’ within the image and reliance on accurate positioning of the cavity and imager. Further, the invention ensures that the temperature profile is based on data taken from the region of the cavity which offers high and, moreover, consistent emissivity enhancement.
The method of the invention could be applied using a static thermal image. However, it is preferable that the method further comprises repeating steps a) to d) at a predetermined frame rate. For example, the thermal imaging device could periodically update the thermal image, preferably at a rate which produces a substantially real-time video of the strip material. The processing steps b) to d) may also be carried out in substantially real-time or each thermal image may be buffered for subsequent processing.
Step b) may be performed in a number of different ways depending for example on the processing capacity available, the geometry of the cavity and/or the field of the imager. If there is plenty of processing capacity and the imaging device views only the cavity, it may be possible to identify the first subset of pixels by selecting all of those pixels in the image having a pixel value greater than a certain threshold, or within a range of limits, or by selecting the N pixels having the highest pixel values. The predetermined criteria need not result in selection of pixels with the highest pixel values: for example, pixels having values around 50% of the highest pixel values in the image might be selected.
In a particularly preferred example, the first subset of pixels is identified by selecting the pixel having the highest pixel value from each of at least two of the columns of the thermal image, preferably about half of the columns, still preferably about 1 out of every 10 columns.
In another preferred example, the first subset of pixels is identified by selecting the pixel having the highest pixel value from each of at least two of the rows of the thermal image, preferably about half of the rows, still preferably about 1 out of every 10 rows.
These methods could be extended to use all of the columns/rows in the thermal image, however it is preferred to limit the number used so as to reduce processing capacity. These methods are particularly preferred in situations where the cavity geometry is such that it is known that the line of optimally-enhanced emissivity will be, respectively, nominally parallel to the rows of the image (“horizontal”) or nominally parallel to the columns of the image (“vertical”).
In step c), the line representing optimal emissivity enhancement can be determined in many ways, depending on the geometry of the cavity and the manner in which the first subset of pixels is selected, for example. In some cases, the line representative of optimal emissivity enhancement in the cavity could comprise the first subset of pixels. This may be the case where the pixels are selected from every column/row, or from closely spaced columns/rows such that merely connecting the pixels accurately defines the desired line.
However, it is preferred that the line representative of optimal emissivity enhancement in the cavity is determined by generating a line which best fits the first subset of pixels, preferably using a least-squares fit. This helps to ensure that the line is not distorted by any anomalous pixels.
The step c) method may also involve knowledge of the cavity geometry: for example, where the cavity is formed by a ‘wedge’ as described above, it is known that the line of optimal emissivity enhancement should be straight, and so a straight line fit can be used. However, the line representative of optimal emissivity enhancement in the cavity need not be rectilinear but could be a polynomial or could comprise more than one linear section.
It should be noted that the line representing optimal emissivity enhancement is an approximation: the actual pixels from which the temperature profile is extracted are selected (using the line) in step d). However, as described below, this second subset of pixels may not be entirely co-incident with the line determined in step c).
It should also be noted that while the ‘optimal’ emissivity enhancement would usually be considered to correspond to ‘maximum’ emissivity enhancement, this need not be the case. It may be found for example, that another region gives more stable enhancement and in some cases this might be considered to be preferable.
In step d), the second subset of pixels can be selected using a variety of techniques. In a preferred example, selecting the second subset of pixels comprises:                (i) identifying pixels nearest to the determined line, the identified pixels forming the second subset.        
This could involve choosing all pixels within a certain distance of the line, or picking the N pixels closest to the line. The selected pixels may additionally be spaced from each other by a certain distance. The second subset of pixels could be the same as the first subset of pixels.
In particular examples, the pixels nearest to the determined line are chosen by selecting the nearest pixel to the determined line from each of at least some of the columns of the thermal image, preferably all of the columns. Alternatively, the pixels nearest to the determined line are chosen by selecting the nearest pixel to the determined line from each of at least some of the rows of the thermal image, preferably all of the rows. As in the case of selecting the first subset of pixels, less than all of the rows/columns could be used in this step, in order to reduce processing capacity—for example using 1 column/row out of every 10.
In another preferred example, the method is further refined and in step d), selecting the second subset of pixels further comprises:                (ii) for each of at least some of the pixels identified in step (i), defining an array of pixels including the identified pixel, comparing the pixel values of the pixels within the array to locate the pixel having the highest pixel value within the array, and replacing the pixel identified in step (i) with the located pixel in the second subset.        
This additional step has been found to significantly improve the appearance of the final temperature map data.
Preferably, the array has a pre-defined size of n×m pixels, n and m being adjustable, for example user-selectable. In a particularly preferred embodiment, the array has a pre-defined size of 5×5 pixels. Advantageously, the array is centred on the identified pixel, although this need not be the case.
Depending on the technique employed in step d), the determined line may automatically lie within the boundaries of the sheet material depicted in the thermal image. However in other examples it may extend beyond and the generated temperature profile might therefore include portions which do not relate directly to the sheet material. In many cases this may be acceptable. However, in order to reduce the amount of processing that is carried out, it is preferable that the method should further comprise:
d1) comparing the pixel values associated with the second subset of pixels with a threshold value to identify one or more edges of the sheet material, terminating the determined line so as not to extend beyond any identified edge(s) and revising the second subset of pixels based on the terminated line.
The temperature profile (based on this revised second subset) would then show only values received from the strip material itself.
Preferably, the threshold value is adjustable, for example user-set. In advantageous alternatives, the threshold value is based on a function of the pixel values associated with the revised second subset of pixels in a previous image frame. This enables the threshold to be dynamically updated and so takes account of changes in the temperature of the material over time. The function may also take account of a user confidence value.
The generated temperature profile could be used in a number of ways. For example, the profile could be monitored for values exceeding a specified limit and an alarm sounded if the limit is passed. Alternatively, the profile could be used to give an indication of changes in the temperature of the sheet material. However, in many cases it is helpful to be able to have a temperature profile which directly relates to position on the sheet material. It is therefore preferable that the method should further comprise:
e) performing a co-ordinate transformation to produce a second temperature profile related to true position along a direction on the sheet material, based on known geometry of the cavity and the thermal imaging device.
Such a profile which compensates for viewing geometry could be used for example to detect anomalies in the sheet material and accurately locate them.
In most situations, the sheet material will be moving while the thermal image(s) are taken and the temperature profiles generated. Preferably, the sheet material comprises a strip having a width transverse to its direction of motion, and the second temperature profile is along the width of the strip.
In order to relate temperature measurements to position on the sheet material in the direction of movement, it is advantageous to have a two-dimensional thermal ‘map’ of the material. Preferably, the method therefore further comprises:
f) generating a temporal thermal map of the sheet material based on the second temperature profile generated for each frame, the map having co-ordinates of time vs. position along a direction of the sheet material, preferably width.
Still preferable would be a map directly related to true spatial location on the sheet material. Therefore, the method advantageously further comprises:
g) monitoring motion of the sheet material and generating a spatial thermal map of the sheet material based on the second temperature profile generated for each frame and the distance moved by the sheet material between frames, the map having co-ordinates of distance along a motion direction of the sheet material vs. position along a direction of the sheet material, preferably width. A motion sensor is provided to measure the speed of the material.
In the case of either the temporal or the spatial thermal map, the map may be generated for only a portion of the sheet material, as desired.
It can also be advantageous to additionally take temperature measurements from outside the region of emissivity enhancement, for example outside the cavity. Here, the temperatures measured are “apparent” temperatures because the emissivity of the material has not been enhanced or stabilised.
Therefore, preferably the method further comprises:
h) defining a second line in the thermal image spaced from and referenced to the determined line representative of optimal emissivity enhancement in the cavity; selecting a third subset of the plurality of pixels based on the second line and generating an apparent temperature profile along the second line derived from the pixel values associated with each of the third subset of pixels.
Advantageously, the second line represents a region of the sheet material outside the region of emissivity enhancement.
Since the location of the second line is dependent on that of the determined line (step c), it too ‘tracks’ movements within the image due to misalignment or coil growth for example.
The second line can be terminated at the strip edges and used to generate an apparent profile directly related to the strip width as well as temporal and spatial thermal maps in the same way as for the line determined in step c).
The data derived from the first determined line can be used in combination with that derived from the second line to compute emissivity profiles or maps. Advantageously, the method further comprises:
l) generating an emissivity profile or emissivity map based on a comparison of the first or second temperature profile, or temporal or spatial thermal map derived from the line determined in step c), with the respective apparent profile or map derived from the second line defined in step h).
This step may be performed in a number of ways. In a first example, for each temperature value in the temperature profile/thermal map, the equivalent black body radiance is calculated using the Planck function and the known wavelength band. The same calculation is performed for each apparent temperature value in the apparent temperature profile/apparent thermal map. The emissivity is the ratio of the two black body radiance values and can be calculated for each point along the profile or in the map. Alternatively, to reduce processing capacity, the emissivity could be calculated by directly ratioing observed radiances along the first and second lines either before or without converting to temperature. With any of these methods, the calculation could be performed by comparing the first and second lines taken from the same thermal image (ie in the same frame), or from different frames. For example, the data from the second line in a first frame could be compared with the data from the first line in a subsequent frame taken after an appropriate interval such that both lines relate directly to the same position on the strip material.
Preferably, the method further comprises:
m) comparing the generated temperature profile, apparent temperature profile, emissivity profile, thermal map or emissivity map with predetermined limits and triggering an alarm signal if a value (eg. temperature, radiance or emissivity) falls outside the predetermined limits. This may be used, for example, to avoid plant fires.
Advantageously, the method further comprises:
n) performing pattern recognition on the generated temperature profile, apparent temperature profile, emissivity profile, thermal map or emissivity map to detect anomalous patterns and triggering an alarm signal if an anomalous pattern is detected. This may be used, for example, to identify contamination or foreign bodies on the strip. Anomalous patterns which may be sought include, for example “holes” of low temperature in the sheet material.
Preferably, the detected radiation is infrared radiation, preferably having a wavelength of approximately 3 to 5 microns or 8 to 14 microns, still preferably approximately 3.3 to 3.5 microns, 3.8 to 4.0 microns, 4.6 to 5.4 microns, 7.6 to 8.4 microns or 7.8 to 8.0 microns. Relatively low wavelengths (3 to 5 microns) are preferred where the strip material is hot (above approximately 200 C), and higher wavelengths (around 8 to 14 microns) where the sheet material is cool (below approximately 200 C). Radiation filters may be provided in order to select the operation bandwith. This may be particularly useful depending on the target material and atmosphere.
Preferably, the pixel values correspond to radiance and step d) comprises converting the radiance values of at least the second subset of pixels to temperature values using the Planck function and the known wavelength band of the radiation. This minimises the processing necessary for the thermal imaging device to carry out, but in alternative examples, the imager could convert the radiance values to temperatures and output these as the pixel values.
Advantageously, the cavity is defined between the sheet material and a roller arranged to support the sheet material. However, suitable cavities could be constructed in many other ways by manipulating the sheet material as desired.
Preferably, the sheet material is wound onto the roller, the roller preferably comprising a mandrel, still preferably a split mandrel of adjustable diameter for facilitating removal from the wound sheet material.
Typically, the method is advantageously used to measure the temperature of metallic sheet materials such as metals or alloys but preferably, the sheet material is aluminium strip, steel strip or bright steel strip.
The invention further provides a temperature-measurement system adapted to perform the above-described method, comprising:
a thermal imaging device arranged to view at least part of a cavity, of which a sheet material forms at least one side, and being adapted to detect radiation emitted by the cavity to thereby generate a thermal image of at least part of the inside of the cavity, the thermal image comprising a plurality of pixels each having a pixel value representative of radiation emitted by a respective region of the cavity; and
a processor adapted to:                identify a first subset of the plurality of pixels whose pixel values meet predetermined criteria;        use the identified first subset of pixels to determine a line on the thermal image representative of optimal emissivity enhancement in the cavity; and        select a second subset of the plurality of pixels based on the determined line and generate a temperature profile along the determined line derived from the pixel values associated with each of the second subset of pixels.        
Preferably, the thermal imaging device comprises an uncooled microbolometer detector array.
Conveniently, the system further comprises a mount adapted to support the thermal imaging device, the mount preferably arranged to enable rotation of the thermal imaging device about at least one axis, preferably two orthogonal axes.
Preferably, the mount enables the thermal imaging device to rotate about two orthogonal axes of which one axis is substantially perpendicular to the direction of motion of the sheet material.
In some examples, the mount is arranged to enable rotation of the thermal imaging device about three orthogonal axes.
Advantageously, the thermal imaging device is contained within a protective housing.
The processor may operate in a stand-alone manner, but preferably, the system further comprises a plant computer to which the results of the processor are output. The plant computer may further receive results from many such processors connected to imagers located around the plant.
Preferably, the processor is connected to the thermal imaging device preferably via one of an ethernet, internet, intranet, TCP/IP, object linking and embedding for process control (OPC), serial port connection or wireless connection.
Advantageously, the processor is connected to the plant computer preferably via one of an ethernet, internet, intranet, TCP/IP, OPC protocol, serial port connection or wireless connection.
Examples of methods and apparatus in accordance with the present invention will now be described with reference to the accompanying drawings.